Relative forward link calibration estimation

ABSTRACT

Techniques for determining a relative Time Calibration (dTcal) value for a mobile device model are disclosed. An example of an apparatus according to the disclosure includes a memory, a receiver configured to receive measurements and a mobile device model information from mobile devices disposed in geographic areas, a processor configured to determine a baseline mobile device model and other mobile devices models based on the measurements, calculate a baseline measurement value based on the measurement values that correspond to the baseline mobile device model, determine difference values based on the baseline measurement value and the other mobile device model measurement values, determine a model specific dTcal value based on the difference values for at least one of the other mobile device models, and store the model specific dTcal value in the memory.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of prior U.S. patent application Ser.No. 14/986,893, filed Jan. 4, 2016, entitled “RELATIVE FORWARD LINKCALIBRATION ESTIMATION,” the entire contents of which is herebyincorporated herein by reference.

BACKGROUND

It is often desirable to know the location of a mobile device such as acellular phone. For example, a location services (LCS) client may desireto know the location of a mobile device in the case of an emergencyservices call or to provide some service to the user of the mobiledevice such as navigation assistance or direction finding. The terms“location” and “position” are synonymous and are used interchangeablyherein. One method of determining the location of mobile device is basedon measurements of the times of signal arrival from multiple antennas.For example, a mobile device may measure time differences in receivedsignals from a plurality of base station antennas. Because positions ofthe base station antennas are known, the observed time differences maybe used to calculate the location of the mobile device. An mobile devicemay make use of a Base Station Almanac (BSA) to perform measurementcalculations and/or may send the measurements to a location server forposition calculation. The term Advanced Forward Link Trilateration(AFLT) is used to describe terrestrial positioning in Code DivisionMultiple Access (CDMA) systems, while the term Observed Time Differenceof Arrival (OTDOA) is used in the context of Wideband CDMA (WCDMA) andLong Term Evolution (LTE) systems. The accuracy in terrestrialpositioning is dependent on synchronization of base station clocks andsignal transmissions. Variations in hardware and installation proceduresmay cause a time bias for a cell signal and decrease the accuracy thepositioning estimate.

SUMMARY

An example of an apparatus for determining a relative Time Calibration(dTcal) value for a mobile device model according to the disclosureincludes a memory, a receiver configured to receive measurements (e.g.,Time of Arrival (TOA)) and a mobile device model information from aplurality of mobile devices disposed in one or more geographic areas, atleast one processor operably coupled to the memory and the receiver,configured to determine a baseline mobile device model and other mobiledevices models based on the measurements, such that the mobile devicesconsist of the baseline mobile device model and the other mobile devicemodels, calculate a baseline measurement value based on the measurementsthat correspond to the baseline mobile device model, determinedifference values based on the baseline measurement value and the othermobile device models measurement values, calculate a model specificdTcal value based on the difference values for at least one of the othermobile device models, and store the model specific dTcal value in thememory.

Implementations of such an apparatus may include one or more of thefollowing features. The at least one processor may be further configuredto calculate a model specific dTcal uncertainty value as a standarddeviation of the plurality difference values for the at least one of theother mobile device models, and store the model specific dTcaluncertainty value in the memory. The at least one processor may beconfigured to determine a device model with a high number ofmeasurements as the baseline mobile device model. The geographic areasmay be a grid located in proximity to a cellular transceiver. Thegeographic areas may be one or more areas corresponding to a receivedsignal strength value. The at least one processor may be furtherconfigured to generate a Forward Link Calibration (FLC) Groupidentification based on the baseline mobile device model. A transmittermay be configured to transmit the model specific dTcal value to the atleast one of the other mobile device models. The at least one processormay be further configured to determine a base station antenna locationbased at least in part on the model specific dTcal value.

An example of a method for determining a relative Time Calibration(dTcal) value for a mobile device model according to the disclosureincludes receiving measurements and mobile device model information frommobile devices disposed in a geographic areas, determining a baselinemobile device model and other mobile devices models based on themeasurements, such that the mobile devices consist of the baselinemobile device model and the other mobile device models, calculating abaseline measurement value based on the measurement values thatcorrespond to the baseline mobile device model, determine differencevalues based on the baseline measurement value and the other mobiledevice model measurement values, determine a model specific dTcal valuebased on the difference values for at least one of the other mobiledevice models, and storing the model specific dTcal value.

Implementations of such a method may include one or more of thefollowing features. Calculating a model specific dTcal uncertainty valueas a standard deviation of the difference values for the at least one ofthe other mobile device models and storing the model specific dTcaluncertainty value. Determining the baseline mobile device model mayinclude determining a device model with a high number of measurements.The geographic areas may be a grid located in proximity to a cellulartransceiver. The geographic areas may be one or more areas correspondingto a received signal strength value. A Forward Link Calibration (FLC)Group identification may be generated based on the baseline mobiledevice model. The model specific dTcal value may be transmitted to theat least one of the other mobile device models. A base station antennalocation may be determined based at least in part on the model specificdTcal value.

An example of a mobile device according to the disclosure includes amemory, a wireless transceiver configured to receive timing measurementinformation, at least one processor operably coupled to the memory andthe wireless transceiver, configured to determine a relative ForwardLink Calibration (FLC) value for the timing measurement information,such that the relative FLC value is based at least in part on a mobiledevice model type, compensate the timing measurement information withthe corresponding relative FLC values, and calculate an estimatedlocation based at least in part on the compensated timing measurementinformation.

Implementations of such a mobile device may include one or more of thefollowing features. The wireless transceiver may be further configuredto provide a cellular transceiver identification information to alocation server, and receive the relative FLC value from the locationserver, such that the FLC value is associated with the cellulartransceiver identification information. The wireless transceiver may beconfigured to receive a FLC Group identification associated with thecellular transceiver identification information. The at least oneprocessor may be configured to determine a set of timing measurementvalues based on the FLC Group identification. The estimated location maybe based on the set of timing measurement values. The relative FLC valuemay be based at least in part on one or more timing measurementconnection parameters. The one or more timing measurement connectionparameters may be at least one of a connection mode, a channel, abandwidth, and a frequency.

An example of a method of determining an estimated location of a mobiledevice according to the disclosure includes determining timingmeasurements with the mobile device, determining a relative Forward LinkCalibration (FLC) value for the timing measurements, such the relativeFLC value is based at least in part on a mobile device model type,compensating the timing measurements with the corresponding relative FLCvalues, and calculating the estimated location of the mobile device withthe compensated timing measurements.

Implementation of such a method may include one or more of the followingfeatures. Determining the relative FLC value may include providing acellular transceiver identification information to a location server,and receiving the relative FLC value from the location server, such thatthe FLC value is associated with the cellular transceiver identificationinformation. A FLC Group identification associated with the cellulartransceiver identification information may be received. A set of timingmeasurement values based on the FLC Group identification may bedetermined. The estimated location of the mobile device may be based onthe set of timing measurement values. The relative FLC value may bebased at least in part on one or more timing measurement connectionparameters. The one or more timing measurement connection parameters mayinclude at least one of a connection mode, a channel, a bandwidth, and afrequency.

An example of an apparatus for determining a relative Time Calibration(dTcal) value for a mobile device model according to the disclosureincludes means for receiving measurements and mobile device modelinformation from mobile devices disposed in a geographic areas, meansfor determining a baseline mobile device model and other mobile devicesmodels based on the measurements, such that the mobile devices consistof the baseline mobile device model and the other mobile device models,means for calculating a baseline measurement value based on themeasurements that correspond to the baseline mobile device model, meansfor determining difference values based on the baseline measurementvalue and the other mobile device model measurement values, means fordetermining a model specific dTcal value based on the difference valuesfor at least one of the other mobile device models, and means forstoring the model specific dTcal value.

An example of an apparatus for determining an estimated location of amobile device according to the disclosure includes means for determiningtiming measurements with the mobile device, means for determining arelative Forward Link Calibration (FLC) value for the timingmeasurements, such the relative FLC value is based at least in part on amobile device model type, means for compensating the timing measurementswith the corresponding relative FLC values, and means for calculatingthe estimated location of the mobile device with the compensated timingmeasurements.

An example of a non-transitory processor-readable storage mediumcomprising instructions for determining a relative Time Calibration(dTcal) value for a mobile device model according to the disclosureincludes code for receiving measurements and mobile device modelinformation from mobile devices disposed in a geographic areas, code fordetermining a baseline mobile device model and other mobile devicesmodels based on the measurements, such that the mobile devices consistof the baseline mobile device model and the other mobile device models,code for calculating a baseline measurement value based on themeasurements that correspond to the baseline mobile device model, codefor determining difference values based on the baseline measurementvalue and the other mobile device model measurement values, code fordetermining a model specific dTcal value based on the difference valuesfor at least one of the other mobile device models, and code for storingthe model specific dTcal value.

An example of a non-transitory processor-readable storage mediumcomprising instructions for determining an estimated location of amobile device according to the disclosure includes code for determiningtiming measurements with the mobile device, code for determining arelative Forward Link Calibration (FLC) value for the timingmeasurements, such the relative FLC value is based at least in part on amobile device model type, code for compensating the timing measurementswith the corresponding relative FLC values, and code for calculating theestimated location of the mobile device with the compensated timingmeasurements.

Items and/or techniques described herein may provide one or more of thefollowing capabilities, and/or other capabilities not mentioned. Mobiledevices may exchange timing information (e.g., Time of Arrival (TOA)information) with a cellular transceiver. Crowdsourcing data includingTOA measurements and location information may be provided from one ormore devices to an almanac. The TOA information is analyzed based on thelocation of the mobile device and the mobile device model type. Abaseline mobile device model type may be selected for a geographicregion. TOA measurement data is sorted based on grid cells. One or morerelative Time Calibration (dTcal) values are determined for the mobiledevice model types. Reverse positioning is conducted to estimate thecellular transceiver's location and determine a FLC value. The FLC valueis relative to the baseline mobile device and varies if other baselinemodels are selected. FLC Groups are identified in cells with the samebaseline mobile device model type. A FLC Group indication is stored inthe almanac. The relative FLC values may be used to compensate TOAmeasurements collected for forward positioning of a mobile device. Twoor more dTcal values associated with different mobile device types maybe stitched together to determine a relative FLC value for respectivepairs of mobile device types. Other capabilities may be provided and notevery implementation according to the disclosure must provide any, letalone all, of the capabilities discussed.

BRIEF DESCRIPTION OF DRAWINGS

Non-limiting and non-exhaustive aspects are described with reference tothe following figures, wherein like reference numerals refer to likeparts throughout the various figures unless otherwise specified.

FIG. 1 is a graphical representation of a Forward Link Calibration (FLC)and a Time Calibration (Tcal) when the range is zero.

FIG. 2 is a graphical representation of the Forward Link Calibration(FLC) and the Time Calibration (Tcal) with an example range greater thanzero.

FIG. 3 is an illustration of multiple mobile devices disposed in ageographic grid.

FIG. 4A is an illustration of the impact of Time Calibration (Tcal) fortwo mobile device models on a reverse position estimate.

FIG. 4B is an illustration of an estimated reverse position of a basestation using the same mobile device model.

FIG. 4C is an illustration of an estimated forward position based on arelative FLC value.

FIG. 4D is a conceptual diagram of stitching relative Tcal (dTcal)values based on one or more relationships between mobile device models.

FIG. 5A is a block diagram of a mobile device that can be used toimplement the techniques discussed herein.

FIG. 5B is a block diagram of a server that can be used to implement thetechniques discussed herein.

FIG. 6 is a block diagram of an example network architecture configuredto communicate with the mobile device of FIG. 5A

FIG. 7A is an illustration of gridding units.

FIG. 7B is an example of a data structure for determining relative FLCvalues.

FIG. 8 is a flow diagram of a process for determining a relative TimeCalibration (dTcal) value.

FIG. 9 is a flow diagram of process for providing relative FLCinformation to a mobile device.

FIG. 10 is a flow diagram of a process for determining an estimatedlocation of a mobile device using relative FLC values.

FIG. 11 is a flow diagram of a process for calculating a stitched dTcalvalue.

DETAILED DESCRIPTION

Some example techniques are presented herein which may be implemented invarious method and apparatuses in a wireless network to possibly providefor or otherwise support positioning techniques for a mobile device.

The location of a mobile device in a wireless network may be determinedbased on measurements of the times of signal arrival from multiple basestation antennas. The accuracy of terrestrial positioning techniques maybe dependent on synchronization of base station clocks and signaltransmissions. Variations in hardware, however may cause variations ininter-cell synchronization on the order of hundreds of nanoseconds. Amobile device may obtain a measure of time synchronization of a forwardlink cell signal by comparing the transmission related times (e.g., Timeof Arrival (TOA)) of a cell signal with a GNSS time associated with acalculated GNSS position, and using the known position of the celltransmitter(s). A time of arrival bias for the cell signal may bedetermined. Determination of the time bias for a cell signal is known asForward Link Calibration (FLC). A FLC estimation is used in terrestrialpositioning to ensure the Time of Arrival (TOA) measurements fromdifferent stations in a network can be aligned. In an embodiment, FLCvalues may be determined for different pairs of base stations in acommunication network, such as described in U.S. patent application Ser.No. 14/146,682, filed on Jan. 2, 2014, and titled “Determination ofDifferential Forward Link Calibration in LTE Networks for Positioning,”the contents of which are incorporated herein by reference. FLCestimation requires known Time Calibration (Tcal) values associated withthe mobile device. In general, Tcal values are time offsets in a time ofarrival solely due to RF, analog, and digital (basebase or other)processing in the receiver in a mobile device. The Tcal may be thedifference between total time delay introduced for time of arrivals ofnetwork signals used for ranging and delay introduced for time ofarrivals of GNSS signals. In operation, Tcal is determined by manyfactors, including the hardware used (antenna, pre-filtering, basebandprocessing), the firmware for low level processing, and the measurementengine software. Other factors such as temperature, voltage changes,bandwidths, and frequencies used may impact the Tcal value. A Tcal valuemay be measured for a particular device, but it is not cost effectivefor a mobile device manufacturer to measure a Tcal value for everymobile device it ships.

Referring to FIG. 1, a graphical representation 100 of the FLC and theTcal when the range is zero is shown. The graphical representation 100illustrates the relative FLC and Tcal values which individuallyrepresent time biases on a base station (e.g., eNB) and a mobile device,relative to GPS timing. FLC is defined as base station transmission timelatency relative GNSS timing. In FIG. 1, an exemplary LTE eNB isintending to transmit subframes at every millisecond, but the actualtransmission may not be exactly aligned with GPS millisecond (ms)boundary due to cable delay or other processing delays. For example, ifthe FLC=100 nanoseconds (e.g., FLC 104), then a LTE frame is sent 100nanoseconds (ns) late after GNSS ms boundary. Typical FLC ranges includeup to ˜100 ns for FLC calibrated eNBs, but are not limited innon-calibrated eNBs.

In an example, the Tcal is defined as the group delay difference of theexemplary LTE receiver minus that of a GNSS receiver, where the groupdelay includes all RF and digital component delays. For example, if anexample Tcal=−21 microseconds (e.g., Tcal 108), the GPS receiver's timenotion is 21 microseconds (μs) later than the exemplary LTE receiver'stime notion such that a LTE timestamp=0 sec corresponds to GPStimestamp=−21 us.

Based on these definitions, FIG. 1 illustrates how the FLC and Tcalvalues impact TOA measurement and range estimation. An example GNSStimestamped TOA measurement at the mobile is given as follows:

TOA=range+Tcal+FLC+measurement errors;

-   -   where both Tcal and FLC are additive terms.

In an example, if the FLC=100 ns (e.g., FLC 104) and the Tcal=−21 μs(e.g., Tcal 108), this implies that an LTE subframe is sent 100 ns lateand was GNSS timestamped early by 21 μs, thus,

TOA=range−20.9 μs+measurement error.

To determine the range (e.g., a range estimate (rangeEst)), the TOAmeasurement is compensated with the FLC and the Tcal values:

rangeEst=TOA−TCAL−FLC.

In reverse positioning applications, where the Tcal is known, TOAinformation is compensated with the Tcal value, and the FLC value isestimated. In forward positioning applications, where the FLC is known,TOA information is compensated with the FLC value, and Tcal value isestimated.

Referring again to the example in FIG. 1, the FLC=100 ns (e.g., FLC 104)and Tcal=−21 μs (e.g., Tcal 108). A range of zero 106 is assumed forsimplification (e.g., a mobile device is colocated at the eNB). A LTEtransmissions from the eNB is delayed by the FLC 104 (e.g., 100 ns afterGNSS ms boundary). The source of the 100 ns delay may be due to hardwareconfigurations such as cable lengths. Since the range of zero 106 isused, the mobile device receives the LTE subframe immediately (e.g., at100 ns) and conducts GNSS time stamping. A GNSS receiver has a largergroup delay value (i.e., a GNSS clock is late compared to a LTE modemclock with Tcal=−21 μs) and thus generates timestamp 21 μs early. As aresult, a first TOA measurement 110 is determined as:

TOA=range+Tcal+FLC;

TOA (modulo 1 ms)=0+100 ns−21 μs;

TOA=−20900 ns.

Referring to FIG. 2, with further reference to FIG. 1, a graphicalrepresentation 200 of the FLC and the Tcal with an example range greaterthan zero is shown. FIG. 2 includes a range value 206. The range valueis exemplary only, and not a limitation. In this example, the rangevalue 206 indicates that the mobile device is 1.5 km from base station(e.g., eNB). A range of 1.5 km is approximately equivalent to 5 μs.Utilizing the FLC 104 and Tcal 108 described in FIG. 1, a second TOAmeasurement 210 is determined as:

TOA (modulo 1 ms)=5 μs+100 ns−21 μs=−15900 ns.

In a forward positioning application, where the TOA is measured, therange estimated may be determine as:

rangeEst=TOA−TCAL−FLC

rangeEst=−15900 ns−(−21 μs)−100 ns=5 μs.

The examples provided in FIGS. 1 and 2 provide examples of absolute FLCand Tcal values. That is, the FLC and Tcal values are compared to a trueGNSS millisecond boundary. The use of the absolute values in FIGS. 1 and2 is provided for the purpose of explaining the relationship between theTOA, range, FLC and Tcal values. As will be described herein, a relativeTcal (dTcal) value may be derived based on the comparison of Time ofArrival (TOA) measurements received from different mobile device modeltypes. Crowdsourcing data received from mobile devices may include TOAmeasurement data and a user location. In an example, the geographic areaaround a cellular transceiver may be partitioned into a grid. The TOAmeasurements may be grouped by geographic areas and mobile device modeltypes. The Tcal values for a particular mobile device model are assumedto be fairly consistent, thus the corresponding TOA measurements for agiven mobile device model in a given geographic area will also be fairlyconsistent. One mobile device model may be selected as a referencemodel. The criteria for the selection may include the number of datapoints (i.e., most popular model), the standard deviation of the TOAmeasurements, average signal strength, or other signal relatedproperties. The mean TOA value for the reference model can be comparedto the TOA measurements obtained for the other mobile devices todetermine TOA difference values. The TOA difference values as comparedto the baseline model type may be collected for multiple geographicareas around the cellular transceiver. Since the TOA measurements areobtained from mobile devices within a known geographic area (i.e., afixed location), the differences in the TOA values are in large part dueto the different Tcal values in the respective mobile devices. Thus,relative Tcal (dTcal) values associated with the reference mobile devicemodel and the other mobile device models may be established and storedin a location almanac (e.g., database). A database of dTcal values canreduce the need to determine an absolute Tcal value in each individualmobile device.

Referring to FIG. 3, an illustration 300 of multiple mobile devicesdisposed in a geographic grid is shown. The illustration 300 includes ageographic area 302 which includes smaller geographic units at variouslocations relative to a cellular transceiver 320. In an example, thesmaller geographic units may be disposed in a grid pattern such asillustrated in FIG. 3. Each of the geographic units may range in size(e.g., 5 m², 10 m², 100 m²). One or more mobile devices may be disposedin the individual grid units. For example, a first grid unit 302 aincludes two mobile devices 310, 312, a second grid unit 302 b includesone mobile device, a third grid unit 302 c includes three mobiledevices, and a fourth grid unit 302 d includes two mobile devices 314,316. Each of the mobile devices within the geographic area 302 isconfigured to communicate with the cellular transceiver 320. The use ofthe cellular transceiver 320 is exemplary only, and not a limitation, asother wireless communication stations such as a local transceiver may beused. The cellular transceiver 320 may be operably connected to analmanac 340 directly or via a network. The communications between themobile devices and the cellular transceiver 320 may be via aLine-of-Sight (LOS) communication path, or via other indirectcommunication paths (e.g., multipath). The disposition of the grid unitsand the corresponding number and dispositions of the mobile deviceswithin the grid units are exemplary only and not a limitation. Thedimensions and shapes of each of grid units 302 a, 302 b, 302 c, 302 dmay vary based on geographical features, propagation patterns, multipathpropagation, the performance of the antenna system associated with thecellular transceiver 320, transmit power, and/or other factors which mayimpact the dispersion of radio frequency energy. Subdividing thegeographic area 302 into the smaller grid units represents the generalconcept of grouping geographic regions into areas which are small enoughto have a fairly consistent relative FLC values, yet large enough tohave a statistically relevant number of samples. For example, becauseFLC values at a position may be affected by multipath, the grid units(and corresponding relative FLC values) may be created based on multiplemeasurements received from the mobile stations located within ageographic area. Multipath refers to effects caused by the reflection ofradio signals by objects. Reflected radio signals are delayed relativeto direct or line of sight signals and reach the mobile station receiverlater than the direct signal. The delay may result in an error inposition determination.

Referring to FIG. 4A, with further reference to FIG. 3, an illustration400 of the impact of Time Calibration (Tcal) for two mobile devicemodels types is shown. The illustration 400 includes two mobile devices410 a, 410 b in geographic area 402. The mobile devices 410 a, 410 brepresent different mobile device model types (e.g., Apple iPhone® vers.4/5/6, Samsung Galaxy®, HTC One®, etc. . . . ), generally designated asmodel ‘A’ and model ‘B’ to simplify the example. The different mobiledevice model types typically will have different Tcal values. The twomobile device model types depicted in FIG. 4A is a generalization of thecrowdsourcing concepts described herein. The crowdsourcing data mayinclude TOA measurement and user location information. No priorknowledge of the mobile device Tcal value, base station location, andFLC values is required. Each of the mobile devices 410 a, 410 b is incommunication with a cellular transceiver 416 (e.g., via a communicationlink 622). The position of the cellular transceiver 416 may bedetermined in part via reverse positioning based on the location of themobile devices 410 a, 410 b and the respective signal exchanges 414 a,414 b. Time of Arrival (TOA) information may be determined based on eachof the signal exchanges 414 a, 414 b. Since each of the mobile devices410 a, 410 b are different models, the respective TOA measurements aredifferent due to variations in hardware and software elements in themobile devices. These differences may be compensated for using Tcalvalues. Due to the different Tcal values, the reverse position of thecellular transceiver 416 may vary based on the TOA differences. Forexample, a first cellular transceiver position 416 a may be based inpart on the first signal exchange 414 a, and a second cellulartransceiver position 416 b may be based in part on a second signalexchange 414 b between the respective mobile devices 410 a, 410 b. TheTOA measurements ‘A’ and ‘B’ are compared to determine the relative Tcalvalue between the two different mobile device models 410 a, 410 b. Asdepicted in FIG. 4A, TOA measurement ‘A’ is greater than TOA measurement‘B’ by a value of ‘C’ 406. Since the measurements are derived frommobile stations within a known geographic area 402, propagation effectsand the corresponding FLC values should be substantially similar samefor both devices. Thus, the value of ‘C’ 406 represents the relativeimpact of the different Tcal values within the two different mobiledevice models 410 a, 410 b. The value ‘C’ 406 illustrates the impact ofthe relative Tcal (dTcal) between model A and model B devices. WhileFIG. 4A only discloses two different mobile devices, in operation theTOA measurements, the location of the cellular transceiver 416, and thecorresponding relationships (e.g., ‘C’ values) between different modelsmay be established with much larger (e.g., statistically relevant)datasets. The value of ‘B’ represents the mean of the TOA measurementsfrom a reference device, and the value ‘C’ represents the TOA differencefor the model ‘A’ device in the geographic area 402. The average TOAdifference (e.g., ‘C’ values) across multiple geographic areas for agiven mobile device model type is the dTcal value for that model type ascompared to the baseline model type. A reverse position of the cellulartransceiver 416 may be determined based on the dTcal values across eachgrid area and for each mobile device model type. The estimated positionof the cellular transceiver 416 and the resulting FLC is the relativeFLC (i.e., relative to the reference mobile device model type).

The geographic area 402, the mobile device model information, the TOAmeasurements, FLC information, dTcal values, and the associated cellulartransceiver position information may be stored in the almanac 340.Additional data may be obtained from multiple mobile devices, includingmultiple mobile device models, such that a matrix of relationships(e.g., dTcal values) may be determined amongst each of the differentdevice models. A relative FLC may be realized by selecting one mobiledevice model as a baseline model, determining the mean of the TOAmeasurements received from the baseline model in a geographic unit,subtracting the baseline mean from the TOA measurements obtained fromother mobile devices in that geographic unit, collecting thesedifferences across multiple geographic units (e.g., each of thegeographic units in the geographic area 302) and finding the averagedifference for each model. That is, each of the other mobile devicemodels may have dTcal values (e.g., ‘C’ values) that are associated withthe comparison to the baseline model. The average and std difference ascompared to the baseline model may be determined for each device modelacross the coverage area of the cellular transceiver 320 (e.g., multiplegeographic units). Thus, the dTcal for a given device model may beexpressed as the average difference (avgDifference) and a dTcalUncertainty value (dTcalUnc) may be expressed the standard deviation ofthe differences (stdDifference) per device model.

Referring to FIG. 4B, with further reference to FIG. 4A, an illustration420 of an estimated reverse position of a base station using two of thesame mobile device model is shown. The illustration 420 includes twomobile devices 421, 422 in the geographic area 402 that are incommunication with a cellular transceiver 416. In this example, the twomobile devices 421, 422 are the same mobile device model (e.g., model‘B’) and thus have similar TCal values. An estimated reverse position427 and FLC value (including uncertainty values) may be based onaggregating the results of multiple reverse positioning events with oneor more mobile devices in multiple geographic areas. For example, afirst estimated position 425 of the cellular transceiver 416 is based inpart on a first TOA measurement exchange 423 with the first mobiledevice 421, and a second estimated position 426 of the cellulartransceiver 416 is based in part on a second TOA measurement exchange424 with the second mobile device 422. The estimated reverse position427 is the aggregation the individual reverse position estimatescalculated from multiple mobile devices of the same model type, acrossmultiple geographic areas. While only two mobile devices 421, 422 areshown in a single geographic area 402, the estimated reverse position427 may be based on lines of position from other geographic areas. Theestimated reverse position 427 and the associated uncertainty value maybe stored in the almanac 340 as the baseline position of the cellulartransceiver 416 for an FLC group. In this example, the FLC group isassociated with the model type ‘B’ mobile devices and may be used insubsequent forward positioning operations.

In an example, the baseline position of the cellular transceiver 416 mayalso be calculated using TOA measurements from other mobile device modeltypes (e.g., other than model type ‘B’), providing the other mobiledevice model types have dTcal values related to the baseline modeldevice type. In this case, the TOA measurements are compensated with thedTcal values derived from the comparison to the TOA measurementscorresponding to model type ‘B’ (i.e., the baseline model type).Multilateration algorithms may be used on the compensated TOAmeasurements to derive the location of cellular transceiver.

Referring to FIG. 4C, with further reference to FIGS. 4A and 4B, anillustration 430 of an estimated forward position based on a relativeFLC value is shown. The illustration 420 includes the cellulartransceiver 416 and a mobile device 436. For the purposes of thisexample, the mobile device 436 is a type ‘A’ mobile device as describedin FIG. 4A. The mobile device 436 is located within a first uncertaintyarea 436′. For the sake of explanation, a second position 432 and asecond uncertainty area 432′ for the mobile device 436 are also shown onFIG. 4A. The second position 432 indicates the estimated position of themobile device if an absolute FLC value is used in conjunction with TOAinformation derived from messages between the mobile device 436 and thecellular transceiver 416. The cellular transceiver 416 is operationallyconnected to a base station almanac (e.g., almanac 340) and isconfigured to provide assistance data to the mobile device 436. In anexample, the cellular transceiver 416 may be an eNB. The assistance datamay include a relative FLC value associated with the geographic area402, an FLC type indicator to identify whether the FLC value is relativeor absolute, and a FLC group index if the FLC type is relative. The FLCtype indicator may be a data field or other data structure used toinform the mobile device that FLC value in the assistance data isrelative or absolute. If the FLC value is relative, the FLC typeindicator may be used to prevent the mobile device from attempting afine time transfer with the relative FLC value. For a relative FLC, theFLC group index may link the cellular transceiver 416 (e.g, an eNB) torelative FLC groups (e.g., group of transceivers with a relative FLCbased on the same reference mobile device model) and enable forwardpositioning based on the specific FLC group.

In operation, the use of a relative FLC value may provide a moreaccurate position estimate as compared to using an absolute FLC value. Aconnection 432 a may be established between the mobile device 436 andthe cellular transceiver 416. The connection 432 a may be acommunication link 622 and configured to support the transfer ofassistance data from a network to the mobile device 436, and thetransfer of location information (e.g., TOA measurements) from themobile device 436 to the network. The connection 432 a may be describedas LTE Positioning Protocol (LPP) or LPP Extensions (LPPe) protocolmessages, but other connections and communication protocols may be used.The connection 432 a may be used to determine a TOA measurement betweenthe cellular transceiver 416 and the mobile device. The mobile device436 may provide an a priori location and device model type informationto the location server 640 via the cellular transceiver 416. Thelocation server 640 is configured to access a previously stored databaseto determine a relative FLC value based on the a priori position of themobile device and the mobile device model type. The cellular transceiver416 may then provide a relative FLC value and an estimated reverseposition 427 of the cellular transceiver to the mobile device. Therelative FLC value is based on the relationship between mobile devicemodels (e.g., model ‘A’ and model ‘B’) as described in FIG. 4A. Forexample, the dTcal value associated with the respective mobile devicemodels (e.g., the value ‘C’). The dTcal value is used to determine acompensated TOA 434. The server 640 is configured to determine acompensated TOA value (compTOA) and a compensated TOA uncertainty value(compTOAUnc) with the appropriate dTcal value.

compTOA(i,ref)=TOA(i)−dTcal(i,ref)

compTOAUnc(i,ref)=sqrt(TOAUnc(i)²+TcalUnc(i,ref)²)

where i is the measuring device and ref is the baseline device model.

For example, the compensated TOA 434 may be determined by applying thedTcal value (e.g., subtracting the value ‘C’) to the measured TOA value(e.g., the value ‘A’). The model ‘A’ mobile device 436 may utilize theestimated reverse position 427 of the cellular transceiver and therelative FLC (i.e., compensated TOA 434) in positioning algorithms todetermine an estimated position of the mobile device 436 and the firstuncertainty area 436′. For example, when a mobile device iscommunicating with multiple cellular transceivers, the mobile device maycollect TOA measurements from the cellular transceivers. The TOAmeasurements may be sorted per FLC groups and the number of TOA's perFLC group. The TOA measurements may be compensated with the relative FLCvalues per FLC group. If a sufficient number of TOA measurements areavailable within a FLC group (e.g., 3 TOA measurements), a positionestimate may be generated (e.g., such as with trilateration methods).Two or more sets of TOA measurements from different FLC groups may beused if a sufficient number of TOA measures from a single group are notavailable.

Referring to FIG. 4D, a conceptual diagram 450 of stitching dTcal valuesbased on one or more relationships between mobile device models isshown. The conceptual diagram includes five different mobile devicemodel types (e.g., type ‘B’ 452, type ‘A’ 454, type ‘X’ 456, type ‘Y’458, and type ‘Z’ 460) and the corresponding relationships between thedevices (e.g., AB 453, BX 455, XY 457, and AZ 459). Each of thedifferent mobile device model types may have different Tcal values andthe relationships represent the corresponding dTcal values. In thisexample, the type ‘B’ model 452 is the baseline model type. The baselinemay represent the most popular mobile device model on a network orwithin a geographic area (e.g., based on unit counts), and/or the mobiledevice model with the highest number of positioning records (e.g., TOAdata) in a geographic area. Other signal parameters, such as deviationto TOA measurements, average signal strength, channel utilization,bandwidth, and frequency may be used in determining a baseline modeltype. As an example, the relationship AB 453 is as described in FIGS.4A-4C including an estimated reverse position 427 of the cellulartransceiver and a relative FLC value based on the compensated TOA 434.The approach described in FIGS. 4A-4C may be applied to the relationshipBX 455 based on the comparison of measurement data obtained from type‘B’ 452 mobile devices and the type ‘X’ 456 mobile devices. The approachmay be repeated for different pairs of mobile device types in a networkor geographic area. For example, the relationship AZ 459 indicates arelative FLC value between type ‘A’ mobile devices and type ‘Z’ mobiledevices. Similarly, the relationship XY indicates a relative FLC valuebetween type ‘X’ 456 mobile devices and type ‘Y’ 458 mobile devices. Theapproach may be extended over several different mobile device modeltypes and geographic areas to determine relative Tcal (i.e., dTcal)values between different model types. Further, the dTcal values frompreviously unrelated (i.e., without relationship data between the modeltypes) may be stitched to create relationships between the previouslyunrelated model types. For example:

dTcal(i,ref)=mean(dTcal(i,j)+dTcal(i,ref))

where j refers to any device model that connects measurements from thisdevice type to the reference device type, and an uncertainty value isdetermined by:

TcalUnc(i,ref)=sqrt(mean(TcalUnc(i,j)² +TcalUnc(j,ref)²)).

In an example, a relationship between model type ‘Z’ 460 and model type‘B’ 452 may be determined by stitching through model type ‘A’ 454 suchthat

dTcal(Z,B)=mean(dTcal(Z,A)+dTcal(A,B)

TcalUnc(Z,B)=sqrt(mean(TcalUnc(Z,A)² +TcalUnc(A,B)²))

The example may be extended to any of the other model device types inFIG. 4D. Stitching the dTcal values for different device model types isparticularly relevant when no dominant (i.e., baseline) model isidentified in a network or geographic area. Further, in that the dTcalvalues are associated with device model types, the dTcal values may beprovided to other networks and/or geographic areas where the devicemodels are used. For example, a device model type may be popular in aparticular market and therefore the dTcal values may be determined froma large dataset. These values may be used in another market where theparticular device model is less popular, or there are just fewer mobilestations overall. In either case, the dTcal values from the first marketmay be used to be used to improve the accuracy of positioning in thesecond market.

Referring to FIG. 5A, a block diagram of a mobile device 500 that can beused to implement relative forward link calibration estimation is show.The mobile device 500 can include or implement the functionality ofvarious mobile communication and/or computing devices; examples include,but are not limited to, tablets, smartphones, portable navigationdevices, network enabled wrist watches, etc., whether presently existingor developed in the future. The mobile device 500 includes a processor511 (or processor core), one or Digital Signal Processors (DSP) 520, andmemory unit 540. The mobile device 500 may also include a wirelesstransceiver 530 configured to send and receive wireless signals 534 viaa wireless antenna 532 over a wireless network. The wireless transceiver530 is connected to a bus 501. Here, the mobile device 500 isillustrated as having a single wireless transceiver 530. However, amobile device 500 can alternatively have multiple wireless transceivers530 and wireless antennas 532 to support multiple communicationstandards such as Wi-Fi, CDMA, Wideband CDMA (WCDMA), Long TermEvolution (LTE), Bluetooth short-range wireless communicationtechnology, etc.

The wireless transceiver 530 may support operation on multiple carriers(waveform signals of different frequencies). Multi-carrier transmitterscan transmit modulated signals simultaneously on the multiple carriers.Each modulated signal may be a Code Division Multiple Access (CDMA)signal, a Time Division Multiple Access (TDMA) signal, an OrthogonalFrequency Division Multiple Access (OFDMA) signal, a Single-CarrierFrequency Division Multiple Access (SC-FDMA) signal, etc. Each modulatedsignal may be sent on a different carrier and may carry pilot, overheadinformation, data, etc.

The mobile device 500 also includes a Global Navigation Satellite System(GNSS) receiver 505 that receives satellite positioning system (SPS)signals 509 (e.g., from SPS satellites) via an SPS antenna 507. The GNSSreceiver 505 can communicate with a single global navigation satellitesystem (GNSS) or multiple such systems. A GNSS can include, but are notlimited to, Global Positioning System (GPS), Galileo, Glonass, Beidou(Compass), etc. SPS satellites are also referred to as satellites, spacevehicles (SVs), etc. The GNSS receiver 505 processes, in whole or inpart, the SPS signals 509 and uses these SPS signals 509 to determinethe location of the mobile device 500. The processor 511, DSP 520, andmemory 540, and/or specialized processor(s) (not shown) may also beutilized to process the SPS signals 509, in whole or in part, and/or tocalculate the location of the mobile device 500, in conjunction withGNSS receiver 505. Storage of information from the SPS signals 509 orother location signals is performed using a memory unit 540 or registers(not shown). While only one processor 511, DSP 520, and a memory unit540 are shown in FIG. 5A, more than one of any, a pair, or all of thesecomponents could be used by the mobile device 500.

The memory unit 540 can include a non-transitory computer-readablestorage medium (or media) that stores functions as one or moreinstructions or code. Media that can make up the memory unit 540include, but are not limited to, RAM, ROM, FLASH, disc drives, etc. Ingeneral, the functions stored by the memory unit 540 are executed by theprocessor 511, DSP 520, or other specialized processors. Thus, thememory unit 540 is a processor-readable memory and/or acomputer-readable memory that stores software (programming code,instructions, etc.) configured to cause the processor 511 to perform thefunctions described. Alternatively, one or more functions of the mobiledevice 500 may be performed in whole or in part in hardware.

A mobile device 500 can estimate its current position within anassociated system using various techniques, based on other communicationentities within view and/or information available to the mobile device500. For instance, a mobile device 500 can estimate its position usinginformation obtained from access points (APs) associated with one ormore wireless local area networks (LANs), personal area networks (PANs)utilizing a short-range wireless communication technology such asBluetooth or ZigBee®, etc., SPS satellites, inertial navigation sensors(e.g., accelerometers, gyroscopes, magnetometer), and/or map constraintdata obtained from a map server or LCI server. One or more of thesetechniques may be used to determine an a priori position of the mobiledevice.

The mobile device includes one or more other input devices 545 such as atouch display, microphone, camera, accelerometers, solid state compass,pressure sensor, magnetometer, gyroscope, and other tactile devices(e.g., buttons, knobs) configured to receive kinetic, electrical and/ormagnetic input.

Referring to FIG. 5B, a computer system 550 to implement relativeforward link calibration estimation is shown. FIG. 5B provides aschematic illustration of one embodiment of a computer system 550 thatcan perform the methods provided by various other embodiments, asdescribed herein, and/or can function as a mobile device or othercomputer system. FIG. 5B provides a generalized illustration of variouscomponents, any or all of which may be utilized as appropriate. FIG. 5Btherefore, broadly illustrates how individual system elements may beimplemented in a relatively separated or relatively more integratedmanner.

The computer system 550 is shown comprising hardware elements that canbe electrically coupled via a bus 555 (or may otherwise be incommunication, as appropriate). The hardware elements may include one ormore processors 560, including without limitation one or moregeneral-purpose processors and/or one or more special-purpose processors(such as digital signal processing chips, graphics accelerationprocessors, and/or the like); one or more input devices 565, which caninclude without limitation a mouse, a keyboard and/or the like; and oneor more output devices 570, which can include without limitation adisplay device, a printer and/or the like. The processor(s) 560 caninclude, for example, intelligent hardware devices, e.g., a centralprocessing unit (CPU) such as those made by Intel® Corporation or AMD®,a microcontroller, an ASIC, etc. Other processor types could also beutilized.

The computer system 550 may further include (and/or be in communicationwith) one or more non-transitory storage devices 575, which cancomprise, without limitation, local and/or network accessible storage,and/or can include, without limitation, a disk drive, a drive array, anoptical storage device, solid-state storage device such as a randomaccess memory (“RAM”) and/or a read-only memory (“ROM”), which can beprogrammable, flash-updateable and/or the like. Such storage devices maybe configured to implement any appropriate data stores, includingwithout limitation, various file systems, database structures, and/orthe like.

The computer system 550 might also include a communications subsystem580, which can include without limitation a modem, a network card(wireless or wired), an infrared communication device, a wirelesscommunication device and/or chipset (such as a BLUETOOTH short-rangewireless communication technology transceiver/device, an 802.11 device,a WLAN device, a WiMax device, cellular communication facilities, etc.),and/or the like. The communications subsystem 580 may permit data to beexchanged with a network (such as the network described below, to nameone example), other computer systems, and/or any other devices describedherein. The communications subsystem 580 may include a receiver 582, atransmitter 583, and one or more antennas 584. The transmitter 583, theantennas 584, and the receiver 582 form a wireless communication module(with the transmitter 583 and the receiver 582 being a transceiver 581).In many embodiments, the computer system 550 will further comprise, ashere, a working memory 585, which can include a RAM or ROM device, asdescribed above.

The computer system 550 also can comprise software elements, shown asbeing currently located within the working memory 585, including anoperating system 590, device drivers, executable libraries, and/or othercode, such as one or more application programs 595, which may comprisecomputer programs provided by various embodiments, and/or may bedesigned to implement methods, and/or configure systems, provided byother embodiments, as described herein. Merely by way of example, one ormore processes described herein might be implemented as code and/orinstructions executable by a computer (and/or a processor within acomputer). Such code and/or instructions can be used to configure and/oradapt a general purpose computer (or other device) to perform one ormore operations in accordance with the described methods.

A set of these instructions and/or code might be stored on anon-transitory computer-readable storage medium, such as the storagedevice(s) 575 described above. In some cases, the storage medium mightbe incorporated within a computer system, such as the computer system550. In other embodiments, the storage medium might be separate from acomputer system (e.g., a removable medium, such as a compact disc),and/or provided in an installation package, such that the storage mediumcan be used to program, configure and/or adapt a general purposecomputer with the instructions/code stored thereon. These instructionsmight take the form of executable code, which is executable by thecomputer system 550 and/or might take the form of source and/orinstallable code, which, upon compilation and/or installation on thecomputer system 550 (e.g., using any of a variety of generally availablecompilers, installation programs, compression/decompression utilities,etc.) then takes the form of executable code.

Substantial variations may be made in accordance with specific desires.For example, customized hardware might also be used, and/or particularelements might be implemented in hardware, software (including portablesoftware, such as applets, etc.), or both. Further, connection to othercomputing devices such as network input/output devices may be employed.

The computer system 550 may be used to perform methods in accordancewith the disclosure. Some or all of the procedures of such methods maybe performed by the computer system 550 in response to processor 560executing one or more sequences of one or more instructions (which mightbe incorporated into the operating system 590 and/or other code, such asapplication programs 595) contained in the working memory 585. Suchinstructions may be read into the working memory 585 from anothercomputer-readable medium, such as one or more of the storage device(s)575. Merely by way of example, execution of the sequences ofinstructions contained in the working memory 585 might cause theprocessor(s) 560 to perform one or more procedures of the methodsdescribed herein.

The terms “machine-readable medium” and “computer-readable medium,” asused herein, refer to any medium that participates in providing datathat causes a machine to operate in a specific fashion. In an embodimentimplemented using the mobile device 500 and/or the computer system 550,various computer-readable media might be involved in providinginstructions/code to processor(s) 511, 560 for execution and/or might beused to store and/or carry such instructions/code (e.g., as signals). Inmany implementations, a computer-readable medium is a physical and/ortangible storage medium. Such a medium may take many forms, includingbut not limited to, non-volatile media, volatile media, and transmissionmedia. Non-volatile media include, for example, optical and/or magneticdisks, such as the memory 540 and storage device(s) 575. Volatile mediainclude, without limitation, dynamic memory, such as the working memory585. Transmission media include, without limitation, coaxial cables,copper wire and fiber optics, including the wires that comprise the bus501, 555, as well as the various components of the communicationssubsystem 580 (and/or the media by which the communications subsystem580 provides communication with other devices).

Common forms of physical and/or tangible computer-readable mediainclude, for example, a floppy disk, a flexible disk, hard disk,magnetic tape, or any other magnetic medium, a CD-ROM, a Blu-Ray disc,any other optical medium, punch cards, paper tape, any other physicalmedium with patterns of holes, a RAM, a PROM, EPROM, a FLASH-EPROM, anyother memory chip or cartridge, a carrier wave as described hereinafter,or any other medium from which a computer can read instructions and/orcode.

Various forms of non-transitory computer-readable media may be involvedin carrying one or more sequences of one or more instructions to theprocessor(s) 511, 560 for execution. Merely by way of example, theinstructions may initially be carried on a magnetic disk and/or opticaldisc of a remote computer. A remote computer might load the instructionsinto its dynamic memory and send the instructions as signals over atransmission medium to be received and/or executed by the mobile device500 and/or computer system 550. These signals, which might be in theform of electromagnetic signals, acoustic signals, optical signalsand/or the like, are all examples of carrier waves on which instructionscan be encoded, in accordance with various embodiments of the invention.

Referring to FIG. 6, an example network architecture 600 configured tocommunicate with the mobile device 500 of FIG. 5A and the computersystem 550 of FIG. 5B is shown. The mobile device 500, may transmitradio signals to, and receive radio signals from, a wirelesscommunication network. In one example, mobile device 500 may communicatewith a cellular communication network by transmitting wireless signalsto, or receiving wireless signals from a cellular transceiver 620 whichmay comprise a wireless base transceiver subsystem (BTS), a Node B or anevolved NodeB (eNB) over wireless communication link 622. Similarly,mobile device 500 may transmit wireless signals to, or receive wirelesssignals from local transceiver 630 over wireless communication link 632.A local transceiver 630 may comprise an access point (AP), femtocell,Home Base Station, small cell base station, Home Node B (HNB) or HomeeNodeB (HeNB) and may provide access to a wireless local area network(WLAN, e.g., IEEE 802.11 network), a wireless personal area network(WPAN, e.g., Bluetooth® network) or a cellular network (e.g. an LTEnetwork or other wireless wide area network such as those discussed inthe next paragraph). Of course it should be understood that these aremerely examples of networks that may communicate with a mobile deviceover a wireless link, and claimed subject matter is not limited in thisrespect.

Examples of network technologies that may support wireless communicationlink 622 are Global System for Mobile Communications (GSM), CodeDivision Multiple Access (CDMA), Wideband CDMA (WCDMA), Long TermEvolution LTE), High Rate Packet Data (HRPD). GSM, WCDMA and LTE aretechnologies defined by 3GPP. CDMA and HRPD are technologies defined bythe 3rd Generation Partnership Project 2 (3GPP2). WCDMA is also part ofthe Universal Mobile Telecommunications System (UMTS) and may besupported by an HNB. Cellular transceivers 620 may comprise deploymentsof equipment providing subscriber access to a wireless telecommunicationnetwork for a service (e.g., under a service contract). Here, a cellulartransceiver 620 may perform functions of a cellular base station inservicing subscriber devices within a cell determined based, at least inpart, on a range at which the cellular transceiver 620 is capable ofproviding access service. Examples of radio technologies that maysupport wireless communication link 622 are IEEE 802.11, Bluetooth (BT)and LTE.

In a particular implementation, cellular transceiver 620 and localtransceiver 630 may communicate with one or more servers 640 (e.g.,computer system 550) over a network 625. Here, the network 625 maycomprise any combination of wired or wireless links and may includecellular transceiver 620 and/or local transceiver 630 and/or servers640. The server 640 is a computer system 550. In a particularimplementation, network 625 may comprise Internet Protocol (IP) or otherinfrastructure capable of facilitating communication between mobiledevice 500 and servers 640 through local transceiver 630 or cellulartransceiver 620. In an implementation, network 625 may comprise cellularcommunication network infrastructure such as, for example, a basestation controller or packet based or circuit based switching center(not shown) to facilitate mobile cellular communication with mobiledevice 500. In a particular implementation, network 625 may compriselocal area network (LAN) elements such as WLAN APs, routers and bridgesand may in that case include or have links to gateway elements thatprovide access to wide area networks such as the Internet. In otherimplementations, network 625 may comprise a LAN and may or may not haveaccess to a wide area network but may not provide any such access (ifsupported) to mobile device 500. In some implementations the network 625may comprise multiple networks (e.g., one or more wireless networksand/or the Internet). In one implementation, network 625 may include oneor more serving gateways or Packet Data Network gateways. In addition,one or more of servers 640 may be an E-SMLC, a Secure User PlaneLocation (SUPL) Location Platform (SLP), a SUPL Location Center (SLC), aSUPL Positioning Center (SPC), a Position Determining Entity (PDE)and/or a gateway mobile location center (GMLC), each of which mayconnect to one or more location retrieval functions (LRFs) and/ormobility management entities (MMEs) in network 625.

In particular implementations, and as discussed below, mobile device 500may have circuitry and processing resources capable of obtaininglocation related measurements (e.g. for signals received from GNSS orother Satellite Positioning System (SPS) satellites 610, cellulartransceiver 620 or local transceiver 630) and computing a position fixor estimated location (e.g., an a priori location) of mobile device 500based on these location related measurements. In some implementations,location related measurements obtained by mobile device 500 may betransferred to a location server such as an enhanced serving mobilelocation center (E-SMLC) or SUPL location platform (SLP) (e.g. which maybe one of the one or more servers 640) after which the location servermay estimate or determine a location for mobile device 500 based on themeasurements. In the presently illustrated example, location relatedmeasurements obtained by mobile device 500 may include measurements ofSPS signals 509 received from satellites belonging to an SPS or GlobalNavigation Satellite System (GNSS) such as GPS, GLONASS, Galileo orBeidou and/or may include measurements of signals (such as 622 and/or632) received from terrestrial transmitters fixed at known locations(e.g., such as cellular transceiver 620). Mobile device 500 or aseparate location server may then obtain a location estimate for mobiledevice 500 based on these location related measurements using any one ofseveral position methods such as, for example, GNSS, Assisted GNSS(A-GNSS), Advanced Forward Link Trilateration (AFLT), Observed TimeDifference Of Arrival (OTDOA) or Enhanced Cell ID (E-CID) orcombinations thereof. In some of these techniques (e.g. A-GNSS, AFLT andOTDOA), pseudoranges or timing differences may be measured at mobiledevice 500 relative to three or more terrestrial transmitters fixed atknown locations or relative to four or more satellites with accuratelyknown orbital data, or combinations thereof, based at least in part, onpilots, positioning reference signals (PRS) or other positioning relatedsignals transmitted by the transmitters or satellites and received atmobile device 500. Doppler measurements may be made to various signalsources such as the cellular transceiver 620, the local transceiver 630,and GNSS satellites 610, and various combination therein. The one ormore servers 640 may be capable of providing positioning assistance datato mobile device 500 including, for example, information regardingsignals to be measured (e.g., signal timing), locations and identitiesof terrestrial transmitters and/or signal, timing and orbitalinformation for GNSS satellites to facilitate positioning techniquessuch as A-GNSS, AFLT, OTDOA and E-CID. For example, the positioninformation based on the Forward Link Calibration estimates describedherein may be provided via the network architecture 600. One or moreservers 640 may comprise an almanac which indicates locations andidentities of cellular transceivers and/or local transceivers in aparticular region or regions such as a particular venue, and may provideinformation descriptive of signals transmitted by a cellular basestation or AP such as transmission power and signal timing. In the caseof E-CID, a mobile device 500 may obtain measurements of signalstrengths for signals received from cellular transceiver 620 and/orlocal transceiver 630 and/or may obtain a round trip signal propagationtime (RTT) between mobile device 500 and a cellular transceiver 620 orlocal transceiver 630. A mobile device 500 may use these measurementstogether with assistance data (e.g. terrestrial almanac data or GNSSsatellite data such as GNSS Almanac and/or GNSS Ephemeris information,relative Forward Link Calibration information) received from the one ormore servers 640 to determine a location for mobile device 500 or maytransfer the measurements to the one or more servers 640 to perform thesame determination.

Referring to FIG. 7A, with further reference to FIG. 3, an illustration700 of gridding units is shown. A geographic area 702 around a cellulartransceiver may be subdivided into smaller geographic units as depictedin FIG. 3. The geographic units may correspond to areas defined byCartesian or Polar coordinates around the cellular transceiver. Forexample, as depicted in the illustration 700, the geographic area 702 issubdivided into a Cartesian grid. The geographic units, however, are notlimited to grids and may include irregularly shaped areas. For example,areas may also be defined by the propagation of electric and radiosignals around the cellular transceiver. Areas based on line-of-sight704 a, 704 b from the transceiver and/or areas based on signal strength706 may be defined. Other propagation considerations may be accountedfor, such as an area impacted by multipath propagation 708. Multiplegrid areas may be combined to form a larger area 710 to create astatistically relevant dataset (e.g., a larger area may encompass morepositioning requests and the corresponding TOA data). An area based onproximity to an access point 712 may be defined. That is, positioningbased on other RF sources such as a local transceiver 630 may besufficient to define a geographic unit. Other areas 714 may also bedefined based on relative FLC values. Thus, the shape and size of ageographic unit may vary based on the areas defined in the dataset.

Referring to FIG. 7B, an example of a data structure 720 for determiningrelative FLC values is shown. The data structure 720 may persist on alocation server 640 and/or almanac 340. The location server 640 and thealmanac 340 may be a single server and thus the terms may be usedinterchangeably. In an example, the location server 640 and the almanac340 may be network servers configured to exchange instructions and data.For example, the almanac 340 may include a database application (e.g.,Oracle®, SQL®, XML) and is configured to receive instructions from thelocation server 640. The almanac 340 may include one or more databasesincluding tables, data fields and relationships.

The tables, data fields and relationships depicted on FIG. 7B areexemplary only and not a limitation as other tables, data fields,relationships, indexing schemes, and other database elements may beused. For example, the location server 640 or almanac 340 are configuredto receive crowdsourcing data including TOA measurement, user location,and mobile device model type data fields. A reference mobile devicemodel type may be identified. The TOA measurements may be sorted basedon grid location and device model type data fields. The location server640 may be configured to determine, for each grid, a dTcal relative tothe reference mobile device model, for each mobile device model type.The location server 640 may be configured to conduct reverse positioningto estimate the cellular transceivers location and an FLC value. Theresulting FLC value is a relative FLC (i.e., relative to the referencedevice model and thus varies if another reference model was selected).The mobile device models with the same reference mobile device model mayform a FLC group. The almanac 340 may be configured store the FLC groupinformation. An example base station table 722 may include fields foridentifying a cellular transceiver (CellID), information regarding theantenna location for the cellular transceiver such a location and anuncertainty value (e.g., antennaLOC, antennaPOSUnc), and FLC value andan FLC Uncertainty value (FLC, FLCUnc), a field to indicate whether theFLC values is a relative FLC value (IsRelativeFLC), and a FLC Groupidentifier (FLCGroupID). The IsRelativeFLC field may be a boolean value(e.g. 0 or 1), and may be used to prevent a mobile device frominitiating a Fine Time Transfer if the FLC value is relative. Otherfields relating to signal parameters may also be used, such as aconnection mode, frequency, and grid identifier. These additional fieldsallow for variation in the dTcal and dTcal Uncertainty values based onthe signal parameters. That is, a relationship between a device modeland a reference model may be dependent on connection mode and/orfrequency, or other signal parameters.

Referring to FIG. 8, a process 800 for providing relative FLCinformation to a mobile device includes the stages shown. The process800 is, however, an example only and not limiting. The process 800 canbe altered, e.g., by having stages added, removed, rearranged, combined,performed concurrently, and/or having single stages split into multiplestages. A location server 640 includes the structure in the computersystem 550 and may be a means for performing the process 800.

At stage 802, the location server 640 is configured to receivemeasurements and mobile device model information from a plurality ofmobile devices disposed in a plurality of geographic areas. In anexample, the measurements may be Time of Arrival (TOA) measurements. Inoperation, an individual mobile device 500 may establish a communicationlink 622 with the cellular transceiver 620. The communication link 622is configured to support the transfer of mobile device modelinformation, position information, and to enable the capture andtransfer of measurements. The location server 640 may be configured tostore the mobile device type information and the measurement data in adata structure. In an example, the measurement data may be compensatedwith an absolute or relative FLC value. The data structure may persiston the location server 640 or on the almanac 340. The location server640 may aggregate the measurements and position information receivedfrom multiple mobile devices. In an example, the location server 640 maybe configured to receive measurements based on a timing exchangemessages with a mobile device.

At stage 804, the location server 640 is configured to determine abaseline mobile device model and other mobile devices models based onthe measurements, wherein the plurality of mobile devices consists ofthe baseline mobile device model and the other mobile device models. Thedata structure may be analyzed or sorted based on the mobile devicemodel information to determine a baseline mobile device model. Thebaseline mobile device model may represent the most popular mobiledevice model on a network or within a geographic area (e.g., based onunit counts), and/or the mobile device model with a high number ofpositioning records (e.g., number of records in the data structure). Ahigh number of measurements (e.g., TOA) is a relative term based oncontent of the data structure and desired performance of a network. Forexample, a high number of measurements may be a threshold valuecorresponding to the expected population of a particular mobile devicemodel (e.g., based on sales information) within a region. Thus, a highnumber need not necessarily be the highest number. The data structuremay include one or more data fields associated with other signalparameters, such as deviations in measurement values, average signalstrength, channel utilization and frequency which may be used indetermining a baseline model type. These data fields may be utilized fordetermining a baseline mobile device model.

At stage 806, the location server 640 is configured to calculate, foreach of the plurality of geographic areas, a baseline measurement valuebased on the measurement values that correspond to the baseline mobiledevice model. In an example, the baseline measurement value is the meanof the TOA measurements corresponding to the baseline mobile devicemodel. The data structure may be gridded based on the estimated positionof the mobile devices when the measurements are determined. The griddinggenerally corresponds to geographic areas with similar RF propagationcharacteristics, and therefore similar FLC values. As the number ofrecords in the data structure increases, the resolution of the griddingmay increase and the corresponding geographic area associated with anindividual grid space may decrease. Thus, a gridding unit may correspondwith a geographic unit, such that the dimensions of the geographic unitmay be dynamic based on the number and/or quality of the records in thedata structure. Within each gridding unit (e.g., geographic area), thelocation server 640 may be configured to determine the mean of themeasurements received from the mobile devices corresponding to thebaseline model type. This result is the baseline measurement value andit is determined for each of the gridding units.

At stage 808, the location server 640 is configured to determine, foreach of the geographic areas, a difference value based on the baselinemeasurement value and the other mobile device model measurement values.In an example, the difference value may be calculated by subtracting thebaseline measurement value from the measurements received from the othermobile device models. The baseline measurement value determined at stage806 is subtracted from each of the measurements received from mobiledevices that are not the baseline model (i.e., other mobile devicemodels) in the respective gridding unit. The location server 640 may beconfigured to perform a subtraction operation on the fields within thedata structure. The difference value is the result of the subtractionoperation and may persist in the data structure as a field within asignal data record.

At stage 810, the location server 640 is configured to determine a modelspecific relative Transmit Calibration (dTcal) value based on thedifference values for at least one of the other mobile device models inthe plurality of geographic areas. In an example, the location server640 may calculate a model specific relative Time Calibration (dTcal)value as the average of the difference values for at least one of theother mobile device models in the plurality of geographic areas. Thelocation server 640 may be configured to select the difference valuesassociated with a mobile device model type and determine the average ofthe resulting values. The average of the difference values for a mobiledevice type is the dTcal value for that mobile device type. Anassociated dTcal uncertainty value may be defined as the standarddeviation of the difference values. The location server 640 isconfigured to store the dTcal value and the dTcal uncertainty value inthe data structure. In an embodiment, the difference values are averagedacross the geographic area (i.e., multiple gridding units), thus thedTcal value is dependent only on the mobile device model type (i.e.,without a further geographic dependence). In another embodiment, thedTcal value may be dependent both a mobile device model type and ageographic area. The dTcal value may be dependent on other signalparameters such a channel, bandwidth, and/or frequency and may be usedto conditionally compensate measurements with the dependencies aresatisfied.

Referring to FIG. 9, a process 900 for providing relative FLCinformation to a mobile device includes the stages shown. The process900 is, however, an example only and not limiting. The process 900 canbe altered, e.g., by having stages added, removed, rearranged, combined,performed concurrently, and/or having single stages split into multiplestages. A location server 640 includes the structure in the computersystem 550 and may be a means for performing the process 900.

At stage 902, the location server 640 is configured to receive griddinginformation from a mobile device via a cellular transceiver 620. Amobile device 500 may establish a communication link 622 with thecellular transceiver 620. The communication link 622 is configured tosupport the transfer of gridding information such as TOA data and mobiledevice model information. In an embodiment, the gridding information mayalso include position information. The position information maycorrespond to an a priori position of the mobile device such as with aninertial navigation system. The position information may be a last knownlocation, or other information that may be used to establish anestimated position of the mobile device. The a priori positioninformation may also include derivative information such as neighborlists, Received Signal Strength Indicator (RSSI) information, or otherinformation which may assist the location server 640 in establishing anestimated location of the mobile device. The mobile device modelinformation may be a numeric or alphanumeric field configured toidentify the make and model of the mobile device. Other signal variablessuch as frequency, bandwidth, and connection mode may also be consideredas gridding information.

At stage 904, the location server 640 is configured to determine a FLCGroup ID based at least in part on the gridding information. In anembodiment, the gridding information includes mobile device model typeinformation and the location server 640 is configured to query the datastructure with an argument including the model type information. Thequery arguments may optionally include other TOA measurement connectionparameters such as frequency, bandwidth, and connection mode. Theresults of the query include the FLC Group ID value that is associatedwith the model type and the baseline model type. In an example, thegridding information may include the FLC Group ID.

At stage 906, the location server 640 is configured to calculate arelative Forward Link Calibration (FLC) value based on the FLC Group ID.The data structure 720 includes a collection of relative FLC valuescorresponding to one or more Cell Id values and FLC Group IDs. Thelocation server 640 may be configured to query the data structure 720with an argument including a Cell ID and a FLC Group ID, and receive thecorresponding relative FLC in the query result. The relative FLC valueis used to compensate TOA measurements obtained by a mobile device ofthe identified mobile device type. At stage 908, the location server 640is configured to provide the mobile device the relative FLC via thenetwork 625 and the communication link 622. In an example, the locationserver 640 may provide multiple relative FLC values corresponding tomultiple Cell IDs in the received TOA measurement information.

Referring to FIG. 10, a process 1000 for determining an estimatedlocation of a mobile device using relative FLC values includes thestages shown. The process 1000 is, however, an example only and notlimiting. The process 1000 can be altered, e.g., by having stages added,removed, rearranged, combined, performed concurrently, and/or havingsingle stages split into multiple stages. A mobile device 500 may be ameans for performing the process 1000.

At stage 1002, a mobile device 500 is configured to determine timingmeasurements. In an example, the timing measurements may be TOAmeasurement information. The mobile device 500 may be within thecoverage area of one or more cellular transceivers 620, and maycommunicate with the location server 640 via the communication link 622and the network 625. The communication link 622 and network 625 areconfigured to support the transfer of mobile device model information,position information, and to enable the capture and transfer of timingmeasurements. In an example, the mobile device may store timingmeasurement information, such as the plurality of timing measurements,locally in the memory 540. In another example, the location server 640is configured to store the timing measurement data.

At stage 1004, the mobile device 500 is configured to determine arelative Forward Link Calibration (FLC) value for the timingmeasurements. The timing measurements include an indication of thecellular transceiver (e.g., Cell ID, cellular transceiver identificationinformation), and the location server 640 may be configured to provideFLC Group information based the respective cellular transceiver. The FLCGroup information includes the corresponding relative FLC value. In anexample, the mobile device 500 is configured to sort the plurality oftiming measurements per FLC Group and the number of timing measurements.Timing measurement sets with less than 1 measurement may be ignored. Forexample, the result of sorting the timing measurements may includeidentifying one or more sets of TOA measurements based on the FLC GroupID:

TOA set 1(FLCGroupID=2)=[TOA(1),TOA(3),TOA(9),TOA(10)]

-   -   where, (TOA(i)=>i is the cell index)

TOA set 2(FLCGroupID=1)=[TOA(2),TOA(4),TOA(6)]

TOA set 3(FLCGroupID=3)=[TOA(5),TOA(7)]

TOA set 4(FLCGroupID=10)=[TOA(8)]=>ignore.

At stage 1006, the mobile device 500 is configured to compensate each ofthe TOA measurements with the corresponding relative FLC values.Specifically, the timing measurements are compensated in view of the FLCGroup ID, and the corresponding mobile device model type from which thetiming measurement was obtained. For example, the compensated TOAmeasurements may be expressed as:

TOAcompByRelativeFLC(i)=TOA(i)−FLC(i) where i is the cell index.

The compensated timing measurement values may be stored locally on themobile device 500, or remotely on the location server 640.

At stage 1008, the mobile device 500 is configured to calculate anestimated location of the mobile device with the compensated timingmeasurements. A set of timing measurement values may be used. In anexample, if a first compensated timing set has a sufficient number ofmeasurements (e.g., no less than 3), the mobile device 500 is configuredto compute a position estimate based on the first compensated timingmeasurement set. An example positioning method includes trilaterationbased on weighted least squares (WLS), which may generate the estimatedlocation of the mobile device and a slack variable. The slack variableis typically close to dTcal value for the corresponding device model. Inanother example, when the timing measurements are TOA measurements, ifthe first compensated TOA set has an insufficient number ofmeasurements, one or more additional compensated TOA values may be usedto calculate the estimated location. In this example, an additionalnumber of slack variables (e.g., one per FLC group) may be generated.The slack variables are expected to be close to dTcal of the devicemodel relative to different reference device model per FLC group. Theestimated location may be displayed, or output to for use with alocation based service application.

Referring to FIG. 11, with further reference to FIG. 4D, a process 1100for calculating a stitched dTcal value includes the stages shown. Theprocess 1100 is, however, an example only and not limiting. The process1100 can be altered, e.g., by having stages added, removed, rearranged,combined, performed concurrently, and/or having single stages split intomultiple stages. A location server 640 includes the structure in thecomputer system 550 and may be a means for performing the process 1100.

At stage 1102, the location server 640 is configured to determine afirst relative Time Calibration (dTcal) value for a first mobile devicemodel, such that the first dTcal value is associated with a secondmobile device model. The dTcal values for the first mobile devicerelative to the second mobile device are calculated as previouslydescribed (i.e., determining the mean TOA difference value), and may bestored in the data structure. The location server 640 is configured toretrieve the corresponding dTcal value based on the relationship betweenthe first mobile device model and the second mobile device model. Forexample, the relationship AZ 459 represents the dTcal value for mobiledevice model type ‘Z’ 460 (e.g., the first mobile device model) that isassociated with mobile device model type ‘A’ 454 (e.g., the secondmobile device model).

At stage 1104, the location server 640 is configured to determine asecond dTcal value for the second mobile device model, such that thesecond dTcal value is associated with a third mobile device model.Referring again to FIG. 4D, the relationship AB 453 represents the dTcalvalue from mobile device model type ‘A’ 454 (e.g., the second mobiledevice model) that is associated with mobile device model type ‘B’ 452(e.g., a third mobile device model).

At stage 1106, the location server 640 is configured to calculate astitched dTcal value for the first mobile device model as the mean ofthe first dTcal value and the second dTcal value, such that the stitcheddTcal value is associated with the third mobile device model. Continuingthe example above, the location server is configured to determine thedTcal(ZB) (e.g., the stitched dTcal value) as the mean of(dTcal(ZA)+dTcal(AB)). The stitching provides a relationship (i.e.,dTcal value) between mobile device model type ‘Z’ 460 and mobile devicemodel type ‘B’ 452 without the need of a direct comparison of the TOAmeasurements obtained from the type ‘Z’ and type ‘B’ devices. Forexample, if the relationship between the type ‘Z’ and the type ‘A’devices is established in a first network or geographic region, and therelationship between the type ‘A’ and the type ‘B’ devices isestablished in a second network or geographic region, then the stitcheddTcal value for the ZB relationship may be used if the type ‘B’ deviceis introduced to the first network or geographic region, and if the type‘Z’ device is introduced into the second network or geographic region.

Reference throughout this specification to “one example”, “an example”,“certain examples”, or “exemplary implementation” means that aparticular feature, structure, or characteristic described in connectionwith the feature and/or example may be included in at least one featureand/or example of claimed subject matter. Thus, the appearances of thephrase “in one example”, “an example”, “in certain examples” or “incertain implementations” or other like phrases in various placesthroughout this specification are not necessarily all referring to thesame feature, example, and/or limitation. Furthermore, the particularfeatures, structures, or characteristics may be combined in one or moreexamples and/or features.

Some portions of the detailed description included herein are presentedin terms of algorithms or symbolic representations of operations onbinary digital signals stored within a memory of a specific apparatus orspecial purpose computing device or platform. In the context of thisparticular specification, the term specific apparatus or the likeincludes a general purpose computer once it is programmed to performparticular operations pursuant to instructions from program software.Algorithmic descriptions or symbolic representations are examples oftechniques used by those of ordinary skill in the signal processing orrelated arts to convey the substance of their work to others skilled inthe art. An algorithm is here, and generally, is considered to be aself-consistent sequence of operations or similar signal processingleading to a desired result. In this context, operations or processinginvolve physical manipulation of physical quantities. Typically,although not necessarily, such quantities may take the form ofelectrical or magnetic signals capable of being stored, transferred,combined, compared or otherwise manipulated. It has proven convenient attimes, principally for reasons of common usage, to refer to such signalsas bits, data, values, elements, symbols, characters, terms, numbers,numerals, or the like. It should be understood, however, that all ofthese or similar terms are to be associated with appropriate physicalquantities and are merely convenient labels. Unless specifically statedotherwise, as apparent from the discussion herein, it is appreciatedthat throughout this specification discussions utilizing terms such as“processing,” “computing,” “calculating,” “determining” or the likerefer to actions or processes of a specific apparatus, such as a specialpurpose computer, special purpose computing apparatus or a similarspecial purpose electronic computing device. In the context of thisspecification, therefore, a special purpose computer or a similarspecial purpose electronic computing device is capable of manipulatingor transforming signals, typically represented as physical electronic ormagnetic quantities within memories, registers, or other informationstorage devices, transmission devices, or display devices of the specialpurpose computer or similar special purpose electronic computing device.

Wireless communication techniques described herein may be in connectionwith various wireless communications networks such as a wireless widearea network (“WWAN”), a wireless local area network (“WLAN”), awireless personal area network (WPAN), and so on. The term “network” and“system” may be used interchangeably herein. A WWAN may be a CodeDivision Multiple Access (“CDMA”) network, a Time Division MultipleAccess (“TDMA”) network, a Frequency Division Multiple Access (“FDMA”)network, an Orthogonal Frequency Division Multiple Access (“OFDMA”)network, a Single-Carrier Frequency Division Multiple Access (“SC-FDMA”)network, or any combination of the above networks, and so on. A CDMAnetwork may implement one or more radio access technologies (“RATs”)such as cdma2000, Wideband-CDMA (“W-CDMA”), to name just a few radiotechnologies. Here, cdma2000 may include technologies implementedaccording to IS-95, IS-2000, and IS-856 standards. A TDMA network mayimplement Global System for Mobile Communications (“GSM”), DigitalAdvanced Mobile Phone System (“D-AMPS”), or some other RAT. GSM andW-CDMA are described in documents from a consortium named “3rdGeneration Partnership Project” (“3GPP”). Cdma2000 is described indocuments from a consortium named “3rd Generation Partnership Project 2”(“3GPP2”). 3GPP and 3GPP2 documents are publicly available. 4G Long TermEvolution (“LTE”) communications networks may also be implemented inaccordance with claimed subject matter, in an aspect. A WLAN maycomprise an IEEE 802.11x network, and a WPAN may comprise a Bluetoothnetwork, an IEEE 802.15x, for example. Wireless communicationimplementations described herein may also be used in connection with anycombination of WWAN, WLAN or WPAN.

In another aspect, as previously mentioned, a wireless transmitter oraccess point may comprise a cellular transceiver device, utilized toextend cellular telephone service into a business or home. In such animplementation, one or more mobile devices may communicate with acellular transceiver device via a code division multiple access (“CDMA”)cellular communication protocol, for example.

In the preceding detailed description, numerous specific details havebeen set forth to provide a thorough understanding of claimed subjectmatter. However, it will be understood by those skilled in the art thatclaimed subject matter may be practiced without these specific details.In other instances, methods and apparatuses that would be known by oneof ordinary skill have not been described in detail so as not to obscureclaimed subject matter.

The terms, “and”, “or”, and “and/or” as used herein may include avariety of meanings that also are expected to depend at least in partupon the context in which such terms are used. Typically, “or” if usedto associate a list, such as A, B or C, is intended to mean A, B, and C,here used in the inclusive sense, as well as A, B or C, here used in theexclusive sense. In addition, the term “one or more” as used herein maybe used to describe any feature, structure, or characteristic in thesingular or may be used to describe a plurality or some othercombination of features, structures or characteristics. Though, itshould be noted that this is merely an illustrative example and claimedsubject matter is not limited to this example.

While there has been illustrated and described what are presentlyconsidered to be example features, it will be understood by thoseskilled in the art that various other modifications may be made, andequivalents may be substituted, without departing from claimed subjectmatter. Additionally, many modifications may be made to adapt aparticular situation to the teachings of claimed subject matter withoutdeparting from the central concept described herein.

Therefore, it is intended that claimed subject matter not be limited tothe particular examples disclosed, but that such claimed subject mattermay also include all aspects falling within the scope of appendedclaims, and equivalents thereof.

What is claimed is:
 1. An apparatus for determining a relative TimeCalibration (dTcal) value for a first mobile device model, comprising: amemory; a receiver configured to receive measurements and a mobiledevice model information from a plurality of mobile devices disposed ina plurality of geographic areas; at least one processor operably coupledto the memory and the receiver, wherein the at least one processor isconfigured to: determine a first model specific dTcal value based on themeasurements from at least one mobile device from the plurality ofmobile devices, wherein the first model specific dTcal value and the atleast one mobile device both correspond to a particular model from themobile device model information; and store the first model specificdTcal value.
 2. The apparatus of claim 1 wherein the at least oneprocessor is further configured to: determine a second model specificdTcal value based on measurements from at least a second mobile devicefrom the plurality of mobile devices, wherein the second model specificdTcal value and the second mobile device both correspond to a secondmodel from the mobile device model information; and store the secondmodel specific dTcal value.
 3. The apparatus of claim 2 wherein the atleast one processor is further configured to determine a third modelspecific dTcal value for a third mobile device base at least in part onthe first model specific dTcal value and the second model specific dTcalvalue.
 4. The apparatus of claim 1 wherein the at least one processor isfurther configured to determine a baseline mobile device model based ona number of measurements received from the plurality of mobile devices.5. The apparatus of claim 4 wherein the at least one processor isfurther configured to generate a Forward Link Calibration (FLC) Groupidentification based on the baseline mobile device model.
 6. Theapparatus of claim 4 wherein the at least one processor is furtherconfigured to calculate a baseline measurement value based onmeasurement values that correspond to the baseline mobile device model.7. The apparatus of claim 6 wherein the first model specific dTcal valuebased at least in part on the baseline measurement value.
 8. Theapparatus of claim 1 wherein the plurality of geographic areas includeone or more areas corresponding to a received signal strength value. 9.A method for determining a relative Time Calibration (dTcal) value for afirst mobile device model, comprising: receiving measurements and amobile device model information from a plurality of mobile devicesdisposed in a plurality of geographic areas; determining a first modelspecific dTcal value based on the measurements from at least one mobiledevice from the plurality of mobile devices, wherein the first modelspecific dTcal value and the at least one mobile device both correspondto a particular model from the mobile device model information; andstoring the first model specific dTcal value.
 10. The method of claim 9further comprising: determining a second model specific dTcal valuebased on measurements from at least a second mobile device from theplurality of mobile devices, wherein the second model specific dTcalvalue and the second mobile device both correspond to a second modelfrom the mobile device model information; and storing the second modelspecific dTcal value.
 11. The method of claim 10 further comprisingdetermining a third model specific dTcal value for a third mobile devicebase at least in part on the first model specific dTcal value and thesecond model specific dTcal value.
 12. The method of claim 9 furthercomprising determining a baseline mobile device model based on a numberof measurements received from the plurality of mobile devices.
 13. Themethod of claim 12 further comprising generating a Forward LinkCalibration (FLC) Group identification based on the baseline mobiledevice model.
 14. The method of claim 12 further comprising calculatinga baseline measurement value based on measurement values that correspondto the baseline mobile device model.
 15. The method of claim 14 whereinthe first model specific dTcal value based at least in part on thebaseline measurement value.
 16. The method of claim 9 wherein theplurality of geographic areas include one or more areas corresponding toa received signal strength value.
 17. An apparatus for determining arelative Time Calibration (dTcal) value for a first mobile device model,comprising: means for receiving measurements and a mobile device modelinformation from a plurality of mobile devices disposed in a pluralityof geographic areas; means for determining a first model specific dTcalvalue based on the measurements from at least one mobile device from theplurality of mobile devices, wherein the first model specific dTcalvalue and the at least one mobile device both correspond to a particularmodel from the mobile device model information; and means for storingthe first model specific dTcal value.
 18. The apparatus of claim 17further comprising: means for determining a second model specific dTcalvalue based on measurements from at least a second mobile device fromthe plurality of mobile devices, wherein the second model specific dTcalvalue and the second mobile device both correspond to a second modelfrom the mobile device model information; and means for storing thesecond model specific dTcal value.
 19. The apparatus of claim 18 furthercomprising means for determining a third model specific dTcal value fora third mobile device base at least in part on the first model specificdTcal value and the second model specific dTcal value.
 20. The apparatusof claim 17 further comprising means for determining a baseline mobiledevice model based on a number of measurements received from theplurality of mobile devices.
 21. The apparatus of claim 20 furthercomprising means for generating a Forward Link Calibration (FLC) Groupidentification based on the baseline mobile device model.
 22. Theapparatus of claim 20 further comprising means for calculating abaseline measurement value based on measurement values that correspondto the baseline mobile device model.
 23. The apparatus of claim 22wherein the first model specific dTcal value based at least in part onthe baseline measurement value.
 24. The apparatus of claim 17 whereinthe plurality of geographic areas include one or more areascorresponding to a received signal strength value.
 25. A non-transitoryprocessor-readable storage medium comprising processor readableinstructions configured to cause one or more processor to determine arelative Time Calibration (dTcal) value for a first mobile device model,comprising: code for receiving measurements and a mobile device modelinformation from a plurality of mobile devices disposed in a pluralityof geographic areas; code for determining a first model specific dTcalvalue based on the measurements from at least one mobile device from theplurality of mobile devices, wherein the first model specific dTcalvalue and the at least one mobile device both correspond to a particularmodel from the mobile device model information; and code for storing thefirst model specific dTcal value.
 26. The storage medium of claim 25further comprising: code for determining a second model specific dTcalvalue based on measurements from at least a second mobile device fromthe plurality of mobile devices, wherein the second model specific dTcalvalue and the second mobile device both correspond to a second modelfrom the mobile device model information; and code for storing thesecond model specific dTcal value.
 27. The storage medium of claim 26further comprising code for determining a third model specific dTcalvalue for a third mobile device base at least in part on the first modelspecific dTcal value and the second model specific dTcal value.
 28. Thestorage medium of claim 25 further comprising code for determining abaseline mobile device model based on a number of measurements receivedfrom the plurality of mobile devices.
 29. The storage medium of claim 28further comprising code for generating a Forward Link Calibration (FLC)Group identification based on the baseline mobile device model.
 30. Thestorage medium of claim 28 further comprising code for calculating abaseline measurement value based on measurement values that correspondto the baseline mobile device model, wherein the first model specificdTcal value based at least in part on the baseline measurement value.